
"""simple docstring"""




def lowercase_    (  _snake_case  ,_snake_case		):
							SCREAMING_SNAKE_CASE__		:			Optional[Any]	 =  ''''''
							for i in table:
														res += inp[i - 1]
							return res

def lowercase_    (  _snake_case		):
							return data[1:] + data[0]

def lowercase_    (  _snake_case  ,_snake_case		):
							SCREAMING_SNAKE_CASE__		:			Any	 =  ''''''
							for i in range(len(_snake_case		)		):
														if a[i] == b[i]:
																					res += "0"
														else:
																					res += "1"
							return res

def lowercase_    (  _snake_case  ,_snake_case		):
							SCREAMING_SNAKE_CASE__		:			Tuple	 =  int("""0b""" + data[0] + data[-1]  ,2		)
							SCREAMING_SNAKE_CASE__		:			int	 =  int("""0b""" + data[1:3]  ,2		)
							return bin(s[row][col]		)[2:]

def lowercase_    (  _snake_case  ,_snake_case  ,_snake_case  ,_snake_case  ,_snake_case		):
							SCREAMING_SNAKE_CASE__		:			Union[str, Any]	 =  message[:4]
							SCREAMING_SNAKE_CASE__		:			Tuple	 =  message[4:]
							SCREAMING_SNAKE_CASE__		:			Tuple	 =  apply_table(_snake_case  ,_snake_case		)
							SCREAMING_SNAKE_CASE__		:			Optional[int]	 =  xor(_snake_case  ,_snake_case		)
							SCREAMING_SNAKE_CASE__		:			List[Any]	 =  apply_sbox(_snake_case  ,temp[:4]		)  # noqa: E741
							SCREAMING_SNAKE_CASE__		:			int	 =  apply_sbox(_snake_case  ,temp[4:]		)
							SCREAMING_SNAKE_CASE__		:			Dict	 =  '''0''' * (2 - len(_snake_case		)) + l  # noqa: E741
							SCREAMING_SNAKE_CASE__		:			Tuple	 =  '''0''' * (2 - len(_snake_case		)) + r
							SCREAMING_SNAKE_CASE__		:			Union[str, Any]	 =  apply_table(l + r  ,_snake_case		)
							SCREAMING_SNAKE_CASE__		:			Optional[Any]	 =  xor(_snake_case  ,_snake_case		)
							return temp + right


if __name__ == "__main__":
					UpperCAmelCase__ :       Dict       				=					input('Enter 10 bit key: ')
					UpperCAmelCase__ :       List[str]       				=					input('Enter 8 bit message: ')

					UpperCAmelCase__ :       Dict       				=					[6, 3, 7, 4, 8, 5, 1_0, 9]
					UpperCAmelCase__ :       str       				=					[3, 5, 2, 7, 4, 1_0, 1, 9, 8, 6]
					UpperCAmelCase__ :       Any       				=					[2, 4, 3, 1]
					UpperCAmelCase__ :       Union[str, Any]       				=					[2, 6, 3, 1, 4, 8, 5, 7]
					UpperCAmelCase__ :       List[str]       				=					[4, 1, 3, 5, 7, 2, 8, 6]
					UpperCAmelCase__ :       Optional[int]       				=					[4, 1, 2, 3, 2, 3, 4, 1]
					UpperCAmelCase__ :       List[Any]       				=					[[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
					UpperCAmelCase__ :       Optional[Any]       				=					[[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

					# key generation
					UpperCAmelCase__ :       int       				=					apply_table(key, paa_table)
					UpperCAmelCase__ :       str       				=					temp[:5]
					UpperCAmelCase__ :       Tuple       				=					temp[5:]
					UpperCAmelCase__ :       List[str]       				=					left_shift(left)
					UpperCAmelCase__ :       Optional[Any]       				=					left_shift(right)
					UpperCAmelCase__ :       Dict       				=					apply_table(left + right, pa_table)
					UpperCAmelCase__ :       Tuple       				=					left_shift(left)
					UpperCAmelCase__ :       Union[str, Any]       				=					left_shift(right)
					UpperCAmelCase__ :       Any       				=					left_shift(left)
					UpperCAmelCase__ :       int       				=					left_shift(right)
					UpperCAmelCase__ :       Dict       				=					apply_table(left + right, pa_table)

					# encryption
					UpperCAmelCase__ :       Tuple       				=					apply_table(message, IP)
					UpperCAmelCase__ :       List[Any]       				=					function(expansion, sa, sa, keya, temp)
					UpperCAmelCase__ :       List[Any]       				=					temp[4:] + temp[:4]
					UpperCAmelCase__ :       Any       				=					function(expansion, sa, sa, keya, temp)
					UpperCAmelCase__ :       Any       				=					apply_table(temp, IP_inv)
					print('Cipher text is:', CT)

					# decryption
					UpperCAmelCase__ :       Optional[Any]       				=					apply_table(CT, IP)
					UpperCAmelCase__ :       Any       				=					function(expansion, sa, sa, keya, temp)
					UpperCAmelCase__ :       List[str]       				=					temp[4:] + temp[:4]
					UpperCAmelCase__ :       Optional[Any]       				=					function(expansion, sa, sa, keya, temp)
					UpperCAmelCase__ :       Tuple       				=					apply_table(temp, IP_inv)
					print('Plain text after decypting is:', PT)












'''simple docstring'''





import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


_UpperCamelCase						:						str  =					datasets.utils.logging.get_logger(__name__)


@dataclass
class  snake_case__      (					datasets.BuilderConfig):
					a_        =					None
					a_        =					"utf-8"
					a_        =					None
					a_        =					None
					a_        =					True  # deprecated
					a_        =					None  # deprecated
					a_        =					10 << 20  # 10MB
					a_        =					None






class  snake_case__      (					datasets.ArrowBasedBuilder):
					a_        =					JsonConfig




					def 		A      (  self  :		Union[str, Any]      )    ->							Optional[int]:
								if self.config.block_size is not None:
											logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''      )
											UpperCAmelCase_      :       Union[str, Any]          =       self.config.block_size
								if self.config.use_threads is not True:
											logger.warning(
											    '''The JSON loader parameter `use_threads` is deprecated and doesn\'t have any effect anymore.'''      )
								if self.config.newlines_in_values is not None:
											raise ValueError('''The JSON loader parameter `newlines_in_values` is no longer supported'''      )
								return datasets.DatasetInfo(features=self.config.features      )




					def 		A      (  self  :		Optional[int]				, _A  :		List[str]      )    ->							int:
								if not self.config.data_files:
											raise ValueError(F"At least one data file must be specified, but got data_files={self.config.data_files}"      )
								UpperCAmelCase_      :       Optional[Any]          =       dl_manager.download_and_extract(self.config.data_files      )
								if isinstance(_A				, (str, list, tuple)      ):
											UpperCAmelCase_      :       List[Any]          =       data_files
											if isinstance(_A				, _A      ):
														UpperCAmelCase_      :       List[str]          =       [files]
											UpperCAmelCase_      :       List[str]          =       [dl_manager.iter_files(_A      ) for file in files]
											return [datasets.SplitGenerator(name=datasets.Split.TRAIN				, gen_kwargs={'''files''': files}      )]
								UpperCAmelCase_      :       Tuple          =       []
								for split_name, files in data_files.items():
											if isinstance(_A				, _A      ):
														UpperCAmelCase_      :       Optional[Any]          =       [files]
											UpperCAmelCase_      :       List[Any]          =       [dl_manager.iter_files(_A      ) for file in files]
											splits.append(datasets.SplitGenerator(name=_A				, gen_kwargs={'''files''': files}      )      )
								return splits




					def 		A      (  self  :		List[Any]				, _A  :		pa.Table      )    ->							pa.Table:
								if self.config.features is not None:
											# adding missing columns
											for column_name in set(self.config.features      ) - set(pa_table.column_names      ):
														UpperCAmelCase_      :       Union[str, Any]          =       self.config.features.arrow_schema.field(_A      ).type
														UpperCAmelCase_      :       int          =       pa_table.append_column(_A				, pa.array([None] * len(_A      )				, type=_A      )      )
											# more expensive cast to support nested structures with keys in a different order
											# allows str <-> int/float or str to Audio for example
											UpperCAmelCase_      :       Dict          =       table_cast(_A				, self.config.features.arrow_schema      )
								return pa_table





					def 		A      (  self  :		Optional[Any]				, _A  :		List[Any]      )    ->							Optional[int]:
								for file_idx, file in enumerate(itertools.chain.from_iterable(_A      )      ):
											# If the file is one json object and if we need to look at the list of items in one specific field
											if self.config.field is not None:
														with open(_A				, encoding=self.config.encoding				, errors=self.config.encoding_errors      ) as f:
																	UpperCAmelCase_      :       Optional[int]          =       json.load(_A      )

														# We keep only the field we are interested in
														UpperCAmelCase_      :       Any          =       dataset[self.config.field]

														# We accept two format: a list of dicts or a dict of lists
														if isinstance(_A				, (list, tuple)      ):
																	UpperCAmelCase_      :       Optional[int]          =       set().union(*[row.keys() for row in dataset]      )
																	UpperCAmelCase_      :       str          =       {col: [row.get(_A      ) for row in dataset] for col in keys}
														else:
																	UpperCAmelCase_      :       Tuple          =       dataset
														UpperCAmelCase_      :       List[str]          =       pa.Table.from_pydict(_A      )
														yield file_idx, self._cast_table(_A      )

											# If the file has one json object per line
											else:
														with open(_A				, '''rb'''      ) as f:
																	UpperCAmelCase_      :       Tuple          =       0
																	# Use block_size equal to the chunk size divided by 32 to leverage multithreading
																	# Set a default minimum value of 16kB if the chunk size is really small
																	UpperCAmelCase_      :       Optional[Any]          =       max(self.config.chunksize // 32				, 16 << 10      )
																	UpperCAmelCase_      :       Tuple          =       (
																	    self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
																	)
																	while True:
																				UpperCAmelCase_      :       Optional[Any]          =       f.read(self.config.chunksize      )
																				if not batch:
																							break
																				# Finish current line
																				try:
																							batch += f.readline()
																				except (AttributeError, io.UnsupportedOperation):
																							batch += readline(_A      )
																				# PyArrow only accepts utf-8 encoded bytes
																				if self.config.encoding != "utf-8":
																							UpperCAmelCase_      :       List[Any]          =       batch.decode(self.config.encoding				, errors=_A      ).encode('''utf-8'''      )
																				try:
																							while True:
																										try:
																													UpperCAmelCase_      :       int          =       paj.read_json(
																													    io.BytesIO(_A      )				, read_options=paj.ReadOptions(block_size=_A      )      )
																													break
																										except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																													if (
																													    isinstance(_A				, pa.ArrowInvalid      )
																													    and "straddling" not in str(_A      )
																													    or block_size > len(_A      )
																													):
																																raise
																													else:
																																# Increase the block size in case it was too small.
																																# The block size will be reset for the next file.
																																logger.debug(
																																    F"Batch of {len(_A      )} bytes couldn't be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}."      )
																																block_size *= 2
																				except pa.ArrowInvalid as e:
																							try:
																										with open(
																										    _A				, encoding=self.config.encoding				, errors=self.config.encoding_errors      ) as f:
																													UpperCAmelCase_      :       List[Any]          =       json.load(_A      )
																							except json.JSONDecodeError:
																										logger.error(F"Failed to read file '{file}' with error {type(_A      )}: {e}"      )
																										raise e
																							# If possible, parse the file as a list of json objects and exit the loop
																							if isinstance(_A				, _A      ):  # list is the only sequence type supported in JSON
																										try:
																													UpperCAmelCase_      :       Optional[int]          =       set().union(*[row.keys() for row in dataset]      )
																													UpperCAmelCase_      :       Any          =       {col: [row.get(_A      ) for row in dataset] for col in keys}
																													UpperCAmelCase_      :       Optional[int]          =       pa.Table.from_pydict(_A      )
																										except (pa.ArrowInvalid, AttributeError) as e:
																													logger.error(F"Failed to read file '{file}' with error {type(_A      )}: {e}"      )
																													raise ValueError(F"Not able to read records in the JSON file at {file}."      ) from None
																										yield file_idx, self._cast_table(_A      )
																										break
																							else:
																										logger.error(F"Failed to read file '{file}' with error {type(_A      )}: {e}"      )
																										raise ValueError(
																										    F"Not able to read records in the JSON file at {file}. "
																										    F"You should probably indicate the field of the JSON file containing your records. "
																										    F"This JSON file contain the following fields: {str(list(dataset.keys()      )      )}. "
																										    F"Select the correct one and provide it as `field='XXX'` to the dataset loading method. "      ) from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																				yield (file_idx, batch_idx), self._cast_table(_A      )
																				batch_idx += 1


